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AFS Advanced Research in Financial Planning Conference 2024

del 18 al 20 de September del 2024

Columbus, Ohio, United States

The Academy of Financial Services (AFS) is excited to be collaborating with FPA to provide an "integrated conference experience" for AFS members this year. The AFS research conference will run for the full 2.5 days of the FPA Conference as part of a dedicated research track bringing the best of AFS and the Journal of Financial Planning (JFP) to you.

  1.  A dedicated Research Room for presentations designed to bring the most relevant research impacting professional financial planners. This includes research sessions sponsored by the JFP and peer-reviewed research papers presented by AFS members. These sessions are CE credit approved.
  2. The winner of the JFP's Montgomery-Warschauer Award for best research from the prior year will present their research.
  3. In the Research Room AFS will coordinate other research content such as a panel discussion with the editors of the 4 major FP research journals explaining to planners and academics the type of research content to be found, how to best consume/digest research and apply it to a FP practice and more.
  4. A new FP Research Shark Tank. Based on the format of the popular TV series a select number of researchers will do 5 minute "pitches" on research that they believe would be significantly impactful for practitioners. Planners and researchers will then vote on the most exciting research proposal.
  5. AFS are co-ordinating 2 additional mini-breakout research rooms where researchers will present additional peer-reviewed, unpublished research selected from the many submissions we received. A timetable of these sessions can be found below.
  6. AFS will manage the research rooms for fully-hybrid attendance with face-to-face or virtual attendance. Although the content will be exceptional, we hope to see many of you in person as the networking, exhibit hall, FPA keynote speakers and other sessions outside of the research cannot be experienced any other way.

Defining AI Algorithms Based on Time and Critical Wealth Levels

miércoles, el 18 de septiembre de 2024 a las 15:30–15:50 ADT
AFS 123
Short Description

An expected utility function of time and wealth is used to define an AI algorithm based on an individual’s time preference and critical wealth levels.  Traditional asset allocation models are based on modern portfolio theory assumptions that individuals are homogenous, wealth maximizers, who have the same time horizon.  These assumptions are questioned beyond the critical wealth level.  Individuals often retire voluntarily once a target wealth level is obtained that optimizes their desired sustainable consumption and amount of leisure time.  The AI algorithm assumes that the critical wealth level is an important reference point that provides a theoretical basis for the start of the reduction in risky asset allocations for individuals who value leisure time and wealth.    

Upload a BLIND copy in Word Document format. Ensure all authors names are removed from the submission. Use the Paper Name + BLIND as the name of the file.

defining_cw_ai_022924_no_title.docx

Lead & Corresponding Author

Brian Boscaljon, PhD, Penn State Erie - The Behrend College
Email Address
Names of authors in order

Brian Boscaljon

Additional Authors

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